Paper/Poster/Presentation Title
Keywords
energy transition; quantitative scenarios; storylines; governance; near-optimal
Location
Session H4: Modeling for Low Carbon Economies
Start Date
19-6-2014 9:00 AM
End Date
19-6-2014 10:20 AM
Abstract
In 2008 United Kingdom adopted an ambitious target to reduce its greenhouse gas emissions by 80% by 2050, compared to the levels of 1990. This is an unprecedented challenge to the power sector and multiple energy-environment-economic modeling activities have been undertaken to inform the energy policy to deliver this low-carbon transition. The role of governance, choices and strategies of the key actors is increasingly acknowledged as an influential determinant of such transition, but traditional energy-environment-economic models can hardly analyze these aspects. This paper proposes a methodological approach to integrating the governance aspects into energy-environment-economic modeling. In the Realizing Transition Pathways project three qualitative storylines of governance were developed through expert and stakeholder engagement. "Market Rules" storyline envisions that market will deliver low-carbon energy transition. "Central Coordination" storyline envisions increased role of the government in shaping this transition. "Thousand Flowers" storyline envisions the wider civic society leading through bottom-up initiatives. These three qualitative storylines are then translated into a range of modeling assumptions for the D-EXPANSE model (Dynamic version of EXploration of PAtterns in Near-optimal energy ScEnarios). D-EXPANSE has the structure of a bottom-up energy-environment-economic model, but is more flexible and allows for systematic exploration of large numbers of power system transition pathways that are cost-optimal and near optimal. Every governance storyline is thus represented by a large number of quantitative pathways and this provides unique insights into the influence of governance on the future UK power system transition.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Linking governance storylines with the D-EXPANSE model to explore the power system transition pathways
Session H4: Modeling for Low Carbon Economies
In 2008 United Kingdom adopted an ambitious target to reduce its greenhouse gas emissions by 80% by 2050, compared to the levels of 1990. This is an unprecedented challenge to the power sector and multiple energy-environment-economic modeling activities have been undertaken to inform the energy policy to deliver this low-carbon transition. The role of governance, choices and strategies of the key actors is increasingly acknowledged as an influential determinant of such transition, but traditional energy-environment-economic models can hardly analyze these aspects. This paper proposes a methodological approach to integrating the governance aspects into energy-environment-economic modeling. In the Realizing Transition Pathways project three qualitative storylines of governance were developed through expert and stakeholder engagement. "Market Rules" storyline envisions that market will deliver low-carbon energy transition. "Central Coordination" storyline envisions increased role of the government in shaping this transition. "Thousand Flowers" storyline envisions the wider civic society leading through bottom-up initiatives. These three qualitative storylines are then translated into a range of modeling assumptions for the D-EXPANSE model (Dynamic version of EXploration of PAtterns in Near-optimal energy ScEnarios). D-EXPANSE has the structure of a bottom-up energy-environment-economic model, but is more flexible and allows for systematic exploration of large numbers of power system transition pathways that are cost-optimal and near optimal. Every governance storyline is thus represented by a large number of quantitative pathways and this provides unique insights into the influence of governance on the future UK power system transition.
